This invention relates generally to centralized generation of reports which compile and/or summarize inventory information stored in a database. In particular, the invention relates to systems and methods for automatically classifying equipment tracked in a database accessible by a computer.
A system for tracking biomedical equipment at a multiplicity of medical facilities has been proposed. In accordance with that proposal, biomedical inventories at a multiplicity of sites will be fed into one centralized database. The inventory information in the database can be processed to generate reports, such as tables and charts, which reports can then be placed on a web server and accessed via a wide area network, e.g., the Internet, by authorized personnel at remote sites, e.g., hospital administrators. The administrators can then use these reports to expedite management of service delivery, asset tracking and asset leveling (i.e., purchasing, renting, etc.).
The proposed multi-site asset management system will be capable of producing reports for individual sites as well as for multiple sites (such as a hospital system). For example, a report can be generated which lists the number of devices of particular types in the inventory of various hospitals belonging to one customer. Alternatively, the devices in inventory can be grouped by modality and/or submodality, the number of devices of each modality/submodality being listed for each hospital. Such inventory listings may be enhanced by the inclusion of various benchmarks, for example, the number of devices of a particular type per operating room or hospital bed for each hospital. Such reports can facilitate asset management by a customer having multiple sites equipped with a multiplicity of types of devices.
The proposed system can also generate charts and tables which show the distribution of the devices of a particular type by manufacturer and model. Such charts and tables can be generated for a particular hospital or a group of hospitals owned by a particular customer. In addition, charts may be generated which display a measured parameter, e.g., average number of breakdowns per maching or mean time between failures, indicative of the relative reliabilities of devices made by different manufacterers. Such reports can provide the customer with a sound basis for making purchase decisions, i.e., which manufacturer to purchase equipment from.
In view of the reliance to be placed on reports summarizing the biomedical equipment in inventory, it is critical that the data input to the system from the hospitals be correct. Correct information cannot be disseminated from a central location unless the data input to the central database is accurate. In a known computerized asset management system, when new equipment is entered into the database, the data entry person is presented with a free-form text field for insertion of the model number with no standardization. [As used herein, the term xe2x80x9cmodel numberxe2x80x9d means any alphanumeric designation which identifies a particular model manufactured by a particular manufacturer and is not limited to include only numbers. In particular, a model number can be a model name having no numbers.] Consequently, data entry personnel may introduce errors (e.g., misspellings) and different data entry persons may adopt varying text to identify the same model number or may introduce punctuation differences. Data entry variances may also arise due to the various ways in which numbers can be expressed, e.g., spelled numbers (e.g., xe2x80x9csixxe2x80x9d) versus Roman numerals (e.g., VI) versus Arabic numbers (e.g., xe2x80x9c6xe2x80x9d). Also one data entry person might enter a Greek lower-case letter (e.g., xe2x80x9cxcex2xe2x80x9d), while another might spell-out the letter (e.g., xe2x80x9cbetaxe2x80x9d), in attempting to enter the same model number. A conventional asset management system is unable to recognize nonstandard model numbers and therefore will be unable to retrieve all relevant data from the database in response to a request that the data for devices having a standardized model number be retrieved from the database.
Further, the conventional asset management system allows each identified piece of equipment to be categorized by entering a device type code. For example, in the case of biomedical equipment, some common device types include the following examples: anesthesia machines, defibrillators, infusion pumps, patient monitors and ventilators. Each piece of equipment is thus classified by manufacturer, model number and device type in the database. However, to be able to categorize a piece of equipment as belonging to a particular device type requires the data entry person to have knowledge of the equipment features and/or capabilities which characterize each device type and knowledge of the corresponding features and/or capabilities of the equipment being categorized, as well as a certain level of analytical skill. Since such knowledge and analytical skill vary from person to person, naturally such a system is susceptible to the input of erroneous device type codes in the centralized database. Again the presence of such erroneous information in the database will result in inaccurate reports based on device type.
Thus there is a need for a method and a system for entering standardized equipment classification data into a centralized database of an asset management system.
The present invention is directed to a method and an apparatus for providing standardized classification of equipment, such as biomedical devices, in an asset (or inventory) management database for inventory analysis and benchmarking. When new equipment is entered into a database, the data entry person will select a predefined manufacturer and model number combination. This will ensure standardized identification of the equipment and proper assignment of a device type code to ensure correct pricing, to minimize maintenance requirements and to facilitate staff skills assessment. By changing the way model numbers are entered in the centralized database from free-form text to a predefined selection or pick list, the model numbers are standardized. In addition, the pick list includes device types associated with the model numbers. Thus when a pick list entry having the desired model number is selected, the corresponding device type code is automatically assigned and included in the database. New manufacturer/model combinations will be checked by a data quality analyst prior to addition to the system to maintain data integrity.
In accordance with the preferred embodiment of the invention, a graphical user interface is used to select classification data from a pick list displayed in a window on a screen. The screen also has a search field which the data entry person fills with a manufacturer query, e.g., the first three letters of the manufacturer""s name. A reference database has records, each record containing manufacturer, model and article type information for classes of articles manufactured by a multiplicity of manufacturers. In response to initiation of a search for the manufacturer specified in the search field, the reference database is searched for all models manufactured by that particular manufacturer. A pick list of the different model names is displayed in the display window on the screen. Each entry includes the same manufacturer identifier, a different model number, and one of multiple article types derived from the reference database. The data entry person can simply click on the entry corresponding to the article to be classified.
In accordance with the preferred embodiment of the invention, in response to selection of an entry from the pick list, a second screen appears having a multiplicity of empty data fields to be filled in by the data entry person and a multiplicity of filled data fields containing the manufacturer identifier, model number and article type from the selected entry. One of the empty data fields is filled in by the date entry person with an article identifier (e.g., a machine serial number) identifying the article being classified (which article has the model number in the selected pick-list entry). The manufacturer identifier, model number and article type for the selected entry are stored in an asset management database in association with the entered article identifier in response to activation by the data entry person. This process is repeated for each article to be tracked by the system, thereby constructing a database which can be used to track assets and make equipment purchase decisions. In particular, inventory and other types of reports can be generated for assets of one or more article type.
In accordance with the disclosed preferred embodiment, the articles being tracked or inventoried are biomedical devices used by hospitals. Digital information characterizing and classifying the assets for a multiplicity of customers owning hospitals and/or other medical facilities are stored in a centralized database. For each model (i.e., class of articles) manufactured by a particular manufacturer, the database contains the manufacturer""s name, the model number, a device type to which the model belongs, a submodality to which the device type belongs, a modality to which the submodality belongs, and a device description corresponding to the device type. Modality groups join equipment with similar functions for repair skills requirements, service level pricing differences and marketing analysis. Submodality groups allow a finer grouping of equipment for inventory analysis and asset management benchmarking. As inventory is added to the database, device type codes of similar types of equipment are automatically assigned to modality and submodality groups. Data on this equipment may then be retrieved from these modality or submodality groups for analysis and benchmarking. Reports can be generated which compile and/or summarize inventory data for one or more device types, for one or more submodalities, or for one or more modalities.
The various device classes (i.e., device type, submodality and modality) are prestored in standardized nomenclature in association with the model number. This process is automated and the relationships between device types and modality/submodality groups are predefined and will remain consistent. Errors from omitting a device type or including an unrelated device type in an analysis will be eliminated.